A new approach is presented to obtain candidate structures from atomic pair distribution function (PDF) data in a highly automated way. It fetches, from web-based structural databases, all the structures meeting the experimenter's search criteria and performs structure refinements on them without human intervention. It supports both X-ray and neutron PDFs. Tests on various material systems show the effectiveness and robustness of the algorithm in finding the correct atomic crystal structure. It works on crystalline and nanocrystalline materials including complex oxide nanoparticles and nanowires, low-symmetry and locally distorted structures, and complicated doped and magnetic materials. This approach could greatly reduce the traditional structure searching work and enable the possibility of high-throughput real-time auto-analysis PDF experiments in the future.
Yang, Long, et al. "Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models." Acta Crystallographica. Section A, Foundations and Advances (Online), vol. 76, no. 3, Apr. 2020. https://doi.org/10.1107/S2053273320002028
Yang, Long, Juhás, Pavol, Terban, Maxwell W., Tucker, Matthew G., & Billinge, Simon J. L. (2020). Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models. Acta Crystallographica. Section A, Foundations and Advances (Online), 76(3). https://doi.org/10.1107/S2053273320002028
Yang, Long, Juhás, Pavol, Terban, Maxwell W., et al., "Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models," Acta Crystallographica. Section A, Foundations and Advances (Online) 76, no. 3 (2020), https://doi.org/10.1107/S2053273320002028
@article{osti_1616487,
author = {Yang, Long and Juhás, Pavol and Terban, Maxwell W. and Tucker, Matthew G. and Billinge, Simon J. L.},
title = {Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models},
annote = {A new approach is presented to obtain candidate structures from atomic pair distribution function (PDF) data in a highly automated way. It fetches, from web-based structural databases, all the structures meeting the experimenter's search criteria and performs structure refinements on them without human intervention. It supports both X-ray and neutron PDFs. Tests on various material systems show the effectiveness and robustness of the algorithm in finding the correct atomic crystal structure. It works on crystalline and nanocrystalline materials including complex oxide nanoparticles and nanowires, low-symmetry and locally distorted structures, and complicated doped and magnetic materials. This approach could greatly reduce the traditional structure searching work and enable the possibility of high-throughput real-time auto-analysis PDF experiments in the future.},
doi = {10.1107/S2053273320002028},
url = {https://www.osti.gov/biblio/1616487},
journal = {Acta Crystallographica. Section A, Foundations and Advances (Online)},
issn = {ISSN ACSAD7},
number = {3},
volume = {76},
place = {Denmark},
publisher = {International Union of Crystallography},
year = {2020},
month = {04}}
Brookhaven National Laboratory (BNL), Upton, NY (United States). National Synchrotron Light Source II (NSLS-II); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division
Grant/Contract Number:
AC52-06NA25396; SC0012704
OSTI ID:
1616487
Alternate ID(s):
OSTI ID: 1632814 OSTI ID: 1678699
Report Number(s):
BNL--216000-2020-JAAM; PII: S2053273320002028
Journal Information:
Acta Crystallographica. Section A, Foundations and Advances (Online), Journal Name: Acta Crystallographica. Section A, Foundations and Advances (Online) Journal Issue: 3 Vol. 76; ISSN 2053-2733; ISSN ACSAD7